Intensive care unit–onset bloodstream infections represent a distinct category of hospital–onset infections: A multicentre, retrospective cohort study. Queensland Critical Care Network (QCCRN)
Bibliographic record
Abstract
Background: The location of onset of bloodstream infections (BSIs) associated with intensive care unit (ICU) admission may influence their clinical and epidemiological characteristics. Methods: A multicentre, retrospective cohort study was conducted in Queensland, Australia, and BSIs associated with ICU admission were identified and classified as community-onset, hospital-onset, or ICU-onset if first isolated within, after 48 hours but within 48 hours of ICU admission, or after 48 hours following ICU admission, respectively. Results: We included 3,540 episodes of ICU-associated BSI, with 1,693 classified as community-onset, 663 hospital-onset, and 1,184 ICU-onset. Compared with hospital-onset BSIs, patients with ICU-onset BSIs were younger, had fewer comorbidities, had lower APACHE II scores, and were more likely male. Patients with ICU-onset BSI were more likely to be surgical admissions and have a primary cardiovascular or neurological diagnosis. The distribution of infective agents varied significantly among community-, hospital-, and ICU-onset BSI groups. The all-cause 30-day case-fatality rates for first-episode community-onset, hospital-onset, and ICU-onset BSIs were 17.1%, 21.7%, and 23.5%, respectively ( p < 0.001). Conclusion: With different epidemiological features and causal pathogens, ICU-onset BSI represents a distinct BSI group arising in hospitalized patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".